##############################
##     run bootstrap on     ##
##  cleaned cces and output ##
## matrices of distribution ##
##       of opinion by      ##
##        party/class       ##
##   at varying thresholds  ##
##############################

rm(list = ls())

# setwd('~/../../Class+Party/')

.libPaths('../rpackages')

library(tidyverse)

args <- commandArgs(TRUE)
print(args)

sim <- as.numeric(args[1])

source('bootstrap_funs.R')

options(dplyr.summarise.inform = FALSE)

cces_allyears <- readRDS('cces_allyears.rds') %>% 
  filter(year != 2010)

cces_allyears <- cces_allyears %>% 
  subset_unique_questions()
cces_allyears <- cces_allyears %>%   # drops leaners and weird cross-party identifiers from being d or r
  mutate(pid3 = case_when(pid7 %in% c('Lean Democrat', 'Strong Democrat', 'Not very strong Democrat') ~ 'Democrat',
                          pid7 %in% c('Lean Republican', 'Strong Republican', 'Not very strong Republican') ~ 'Republican',
                          TRUE ~ pid3))

issuetopics <- cces_allyears %>% 
  select(question, year, pap_topic, topic_3, topic_6) %>% 
  distinct() %>% 
  arrange(question)

classthresholds <- c(5, 10, 20, 25, 33)
parties <- c('dem', 'rep', 'all')

ptm <- proc.time()

output <- list()

for (s in c(sim*2, (sim*2)+1)) {
  set.seed(s)
  
  for (k in classthresholds) {
    boot_cces <- boot_sample_cces(cces_allyears, quantile = k/100)
    
    boot_cces$pid_new <- NA
    boot_cces$pid_new[boot_cces$pid3 %in% c('Republican', 'Democrat')] <- boot_cces$pid3[boot_cces$pid3 %in% c('Republican', 'Democrat')]
    boot_cces$pid_new[boot_cces$pid3 %in% c('Independent', 'Other')] <- 'Independent/Other'
    boot_cces <- boot_cces[,names(boot_cces) != 'pid3']
    
    boot_cces <- boot_cces %>% 
      drop_na(opinion)
    
    
    # class analysis
    
    boot_cces$faminc_group <- NA
    boot_cces$faminc_group[boot_cces$faminc_bottom == 1] <- 'bottom'
    boot_cces$faminc_group[boot_cces$faminc_top == 1] <- 'top'
    boot_cces$faminc_group[boot_cces$faminc_middle == 1] <- 'middle'
    
    
    group_opinions <- boot_cces %>%
      filter(pid_new != 'Independent/Other') %>% 
      drop_na(pid_new, faminc_group) %>% 
      group_by(pid_new, faminc_group, question) %>% 
      summarize(opinion = sum(opinion) / n()) %>% 
      ungroup() %>% 
      bind_rows(boot_cces %>%
                  drop_na(faminc_group) %>% 
                  group_by(faminc_group, question) %>% 
                  summarize(opinion = sum(opinion) / n()) %>% 
                  mutate(pid_new = 'All') %>% 
                  ungroup()) %>% 
      mutate(party_income = paste(pid_new, faminc_group, sep = '_')) %>% 
      select(-pid_new, -faminc_group) %>% 
      spread(key = party_income, value = opinion) %>% 
      arrange(question) %>% 
      column_to_rownames('question')
    
    for (p in c('all', 'dem', 'rep')) {
      pname <- case_when(p == 'all' ~ 'All',
                         p == 'dem' ~ 'Democrat',
                         p == 'rep' ~ 'Republican')
      
      output[[paste(p, 'inctop', k, 'sim', s, sep = '_')]] <-  group_opinions[,paste(pname, 'top', sep = '_')]
      output[[paste(p, 'incmiddle', k, 'sim', s, sep = '_')]] <-  group_opinions[,paste(pname, 'middle', sep = '_')]
      output[[paste(p, 'incbottom', k, 'sim', s, sep = '_')]] <-  group_opinions[,paste(pname, 'bottom', sep = '_')]
      
    }
    
  }
}

print((proc.time() - ptm)/60)

saveRDS(output,
        paste0('bootstrap_out/leanerclassthresholds/leaners_boot_', sim, '.RDS'))
